WO2016068742A1 - Procédé et système de positionnement de terminal mobile dans des bâtiments - Google Patents

Procédé et système de positionnement de terminal mobile dans des bâtiments Download PDF

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Publication number
WO2016068742A1
WO2016068742A1 PCT/RU2014/000822 RU2014000822W WO2016068742A1 WO 2016068742 A1 WO2016068742 A1 WO 2016068742A1 RU 2014000822 W RU2014000822 W RU 2014000822W WO 2016068742 A1 WO2016068742 A1 WO 2016068742A1
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WIPO (PCT)
Prior art keywords
mobile terminal
data
inertial
positions
local coordinate
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Ceased
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PCT/RU2014/000822
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English (en)
Russian (ru)
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WO2016068742A8 (fr
Inventor
Геннадий Михайлович БЕРКОВИЧ
Леонид Викторович ПУРТО
Владимир Александрович СВИРИДЕНКО
Руслан Александрович БУДНИК
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InvenSense International Inc
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InvenSense International Inc
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Priority to US15/523,207 priority Critical patent/US10341982B2/en
Priority to PCT/RU2014/000822 priority patent/WO2016068742A1/fr
Publication of WO2016068742A1 publication Critical patent/WO2016068742A1/fr
Publication of WO2016068742A8 publication Critical patent/WO2016068742A8/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
    • H04W64/003—Locating users or terminals or network equipment for network management purposes, e.g. mobility management locating network equipment
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
    • G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
    • G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
    • G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
    • G01C21/1654—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments with electromagnetic compass
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
    • G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
    • G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
    • G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
    • G01C21/1656—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments with passive imaging devices, e.g. cameras
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/20—Instruments for performing navigational calculations
    • G01C21/206—Instruments for performing navigational calculations specially adapted for indoor navigation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13—Receivers
    • G01S19/24—Acquisition or tracking or demodulation of signals transmitted by the system
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42—Determining position
    • G01S19/48—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system
    • G01S19/49—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system whereby the further system is an inertial position system, e.g. loosely-coupled
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/01—Determining conditions which influence positioning, e.g. radio environment, state of motion or energy consumption
    • G01S5/018—Involving non-radio wave signals or measurements
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
    • G01S5/0257—Hybrid positioning
    • G01S5/0258—Hybrid positioning by combining or switching between measurements derived from different systems
    • G01S5/02585—Hybrid positioning by combining or switching between measurements derived from different systems at least one of the measurements being a non-radio measurement
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
    • G01S5/0278—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves involving statistical or probabilistic considerations
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H04W4/025—Services making use of location information using location based information parameters
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/33—Services specially adapted for particular environments, situations or purposes for indoor environments, e.g. buildings
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S2205/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S2205/01—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations specially adapted for specific applications
    • G01S2205/02—Indoor

Definitions

  • the invention relates to navigation, and more particularly, to navigation within buildings.
  • Positioning by the signals of navigation satellites has worked well in open areas, but it is practically inoperative in rooms. The reason is that the satellite signal is so weakened after passing through the walls and overlapping buildings that in most cases its level is insufficient for the satellite receiver to receive it. Even in cases where the satellite signal is not so weak, it is distorted by reflections from walls and other objects indoors (the effect of multipath propagation of radio waves), which leads to unacceptably large positioning errors.
  • Data from non-inertial sensors in this method can be considered Wi-Fi signal levels from access points monitored by a mobile terminal, magnetometer readings, an image received from a mobile phone’s camcorder, and any other information available on a mobile device to directly or indirectly identify a user's location.
  • the disadvantage of this method is the need for full mapping of the room, which is unprofitable and not always possible.
  • Another disadvantage of this method is the need to indicate the coordinates of known positions during the training, which requires the use of a different, more accurate method for determining the coordinates of a mobile terminal in a room.
  • the indicated technical solution describes a positioning device consisting of passive sensors of a mobile terminal, a laptop computer and a module for assessing the probability of matching an unknown position of one of the known positions.
  • the system described in this technical solution is closest to the proposed one and is selected as a prototype.
  • This analysis is to refine the trajectory calculated using inertial data, to compare the tracks thus collected and to link them into a continuous map by combining those sections of the tracks where similar non-inertial data were observed.
  • the advantage of this approach is more accurate mapping, achieved through analysis and refinement of the navigation data used.
  • Another advantage of the method is the ability to map large rooms that cannot be quickly reached from the outside (in particular, from the street).
  • the disadvantage of this method is a slightly better, but still weak protection against low-quality data, as well as the unresolved question of how to determine and coordinate the coordinates of the mapped data. noisysy map data with inaccurate linkage to the plan when coupling them into a single map lead to an increase in the mapping error. Using such a card leads to large positioning errors.
  • the said application also describes a positioning device for a mobile terminal, consisting of a set of comparators analyzing isolated streams of inertial and non-inertial data for the repetition of the same or similar values spaced over a certain time interval and detecting the excess of similarity of data of a certain threshold.
  • the objective of the present invention is to provide a method for positioning a mobile terminal inside buildings, as well as a system for implementing this method.
  • a feature of the proposed solution is the lack of a priori information before starting positioning, such as, for example, a map of the distribution of a radio field or a magnetic field in a building. Creating maps of the distribution of parameters of physical fields in the room is carried out directly in the process of the proposed method of positioning. Moreover, in one of the implementations of the proposed method does not even require a building plan.
  • the technical result achieved as a result of the implementation of the proposed method is to prevent the accumulation of mapping errors as you link some mapping data with other data.
  • the error accumulation is prevented by linking the data being mapped to local coordinate systems associated with well identifiable positions, the relative position of which is determined with greater accuracy than the relative position between other positions. Greater accuracy in determining the relative position between well-identified positions can be achieved by statistical averaging of a large amount of data collected by different users using mobile terminals with inertial sensors of various types. An additional advantage is that this does not imply the availability of a building plan.
  • the advantage of the proposed system is the distinction between locally mapped fragments of the room, implemented through the introduction of data warehousing into the system.
  • Each of the storages is uniquely associated with a well-identifiable position and its identifying trait, or with a group of well-identifiable positions and traits. Due to this, data collection is effectively implemented from many users moving around the building with various mobile terminals, since data from different users are identified by a unique feature and end up in the corresponding storage, after which they jointly participate in further processing. This reduces the computational cost when implementing the proposed method.
  • the method for positioning a mobile terminal inside buildings includes the following steps: identifying signs identifying the location of the mobile terminal at a specific position based on data received from at least one inertial and non-inertial sensor during the movement of at least one mobile terminal; determine and save the trajectory of the motion of the aforementioned mobile terminal in a local coordinate system associated with the aforementioned position and data from non-inertial sensors; form statistically averaged transformation parameters of the local coordinate systems of the mobile terminal at the positions determined during terminal movement; form at least one map of the distribution of the output values of non-inertial sensors based on the data obtained in the previous step; determine the position of the above mobile terminal based on the data obtained in the previous step.
  • the parameters of the transformation of the local coordinate system for positions corresponding to the above signs are determined, and these actions are repeated one and more than once;
  • At least one map of the distribution of output values is generated, and the coordinates of the positions estimated in local coordinate systems obtained during the movement of at least one terminal are converted into a global coordinate system;
  • the position of the mobile terminal is further refined.
  • a sign identifying the location of the mobile terminal at a specific position is a sequence of measurements over a specific time interval.
  • the number of local coordinate systems is less than the number of identified features.
  • the positions associated with them are combined into a common zone.
  • position estimation is performed using a particle filter.
  • the mobile terminal is a device capable of providing information and moving with the user.
  • the mobile terminal is a smartphone or tablet, or laptop, or car navigator.
  • the inertial sensor is a gyroscope or accelerometer
  • the non-inertial sensor is a magnetometer or a compass, or a barometer, or a video sensor, or a microphone, or a radio receiver.
  • the invention can be implemented as a device for positioning a mobile terminal inside buildings, including: one or more command processing devices, one or more data storage devices, one or more programs, where one or more programs are stored on one or more data storage device and are executed on one or more processors, moreover, one or more programs includes the following instructions: identify signs identifying the location of the mobile terminal in a certain position, based on data received from at least one inertial and non-inertial sensor during the movement of at least one mobile terminal; determining and storing the motion path of the aforementioned mobile terminal in a local coordinate system associated with the aforementioned position and data from non-inertial sensors; form statistically averaged transformation parameters of the local coordinate systems of the mobile terminal at the positions determined during terminal movement; form at least one map of the distribution of the output values of non-inertial sensors based on the data obtained in the previous step; determine the position of the above mobile terminal based on the data obtained in the previous step.
  • the invention may be implemented as a positioning system for a mobile terminal inside buildings, including:
  • At least one computer system at least one coordinate converter connected to the above computer system;
  • one or more data stores connected to at least one coordinate transformer; at least one feature definition module, connected to one or more of the above data storage; one or more sensors connected by the above computer system and a feature detection module; a module for calculating the probability of finding this device in a certain position, connected to the above computer system.
  • one or more data stores and at least one coordinate transformer are located on a remote server or cloud resource.
  • communication between at least one computer system and at least one feature determination module is carried out via wireless communication.
  • communication between the components of the system is through wireless communication
  • FIG. 1 shows the process of moving a mobile terminal 191 along a continuous path 190 in the room 192 to be mapped.
  • the mobile terminal 191 was in unknown but well identifiable positions 101 and 103, its direction of movement, as well as fragments of the path to and after passing these positions.
  • the mobile terminal was moved along trajectory 1 10 through position 101 in the direction 1 11, and then within the same fragment of the trajectory through position 103 in the direction 1 12.
  • the mobile terminal moved along trajectory 120 first through position 103 in the direction 122, then through position 101 in the direction 121.
  • the mobile terminal was moved through position 101 along the path 130 in the direction 131 and along the path 140 in the direction 141.
  • FIG. 2 illustrates the process of distinguishing features.
  • the trajectory 220 of the mobile terminal in the room 221 is shown.
  • Positions 207 and 208, the corresponding coordinate systems 205 and 206, as well as the directions of movement 209 and 210 are shown.
  • the time axis 200 is shown.
  • Position 207 is designated as unknown with high confidence position P1 (202), and position 208 - as an unknown position P2 (204) identified with high reliability.
  • the mobile terminal identifies a visit to position P1 at time tj (211), and position P2 at time t 2 (212). At these time points, the characteristics are measured from the output of the sensors of the mobile terminal, respectively C (t]), designated as 201, and C (t 2 ), indicated as 203.
  • Curly brackets 213 and 214 show fragments of the trajectory of the mobile terminal in the time interval, including the moment of detection of the sign, that is, at moments t] (21 1) and t 2 (212).
  • FIG. 3 illustrates the process of converting local coordinate systems.
  • a path 301 is shown along which a mobile terminal moves. Shown are the positions of the mobile terminal at successive times. The corresponding entries are designated as P1 (304) and P2 (305).
  • Local (Cartesian) coordinate systems 310 and 31 1 are also shown, the centers of which are respectively in the positions P1 and P2.
  • the axes of the coordinate system 310 are designated as x (312) and y (313), the coordinate systems 311 are designated as x '(314) and y' (315).
  • the transfer parameters of the origin of the coordinates of the second local system relative to the first are denoted as a (320) and b (321), and the angle of rotation of the second local system relative to the first system is denoted as ⁇ (323).
  • FIG. 4 is a block diagram of a positioning system of a mobile terminal indoors.
  • the system consists of many sensors of a mobile terminal 401, a computer 402, and a probability calculation module 403. Additionally, a feature generation module 410, an array of data warehouses 41 1, and a coordinate transformer 412 are included in the system.
  • FIG. 5 illustrates the use of data warehouses in the positioning system of a mobile terminal. Shown are fragments of a mapped room in the form of three regions: a region 503 with a local coordinate system 502 associated with a well-identified position 501, a region 506 with a local coordinate system 505 associated with a well-identified position 504, and a region 509 with a local coordinate system 508 associated with well-identified 507.
  • the orientation of the local coordinate systems 502, 505 and 508 can be unambiguously defined in the global coordinate system 510.
  • Regions 503, 506, and 509 define an approximate demarcation between locally mapped fragments of a room.
  • data related to the local coordinate system 502 is stored in the storage 511
  • data related to the local coordinate system 505 is stored in the storage 512
  • data related to the local coordinate system 508 is stored in the storage 513.
  • the present invention in its various embodiments can be implemented in the form of a method (including that implemented on a computer), in the form of a system, in the form of a device or computer-readable medium containing instructions for performing the above method.
  • a device means a computer device, a computer (electronic computer), CNC (numerical program control), PLC (programmable logic controller) and any other devices that can perform a given, well-defined sequence of operations (actions, instructions).
  • command processing device an electronic unit or an integrated circuit (microprocessor) that executes machine instructions (programs).
  • the command processing device reads and executes machine instructions (programs) from one or more data storage devices.
  • Data storage devices may include, but are not limited to, hard disks (HDDs), flash memory, ROM (read only memory), solid state drives (SSDs), and optical drives.
  • a program is a sequence of instructions intended for execution by a control device of a computer or a device for processing commands.
  • the inventive method of positioning a mobile terminal inside buildings and implementing its system can be implemented as described below.
  • a mobile terminal is understood to mean any device that can move with the user, and which is capable of providing the user with information, in particular information about his position.
  • An example of a mobile terminal is devices such as smartphones, tablet computers, mobile phones, laptops, netbooks, pedestrian and car navigators, trackers, and the like. These also include devices worn on the user's body, among which you can specify "smart glasses” (for example, Google Glass), "smart watches” or smart watches (for example, Samsung Galaxy Gear), devices for sports and fitness, and others.
  • the list of sensors on a mobile terminal may include inertial sensors (for example, gyroscopes and accelerometers), a magnetic field sensor (magnetometer), a compass, a pressure sensor (barometer), an image sensor (camera), a microphone, a touch screen, telecommunication and navigation modules such as WiFi, BLE, NFC, 3G / LTE, GPS / GNSS modules and others.
  • the mobile terminal is equipped with at least part of these sensors and modules, including inertial (e.g. accelerometer and gyroscope) and non-inertial (e.g. WiFi module, magnetometer and others) sensors.
  • inertial e.g. accelerometer and gyroscope
  • non-inertial e.g. WiFi module, magnetometer and others
  • the output signals of these sensors and modules are recorded during terminal movements.
  • these may include accelerations and angular velocities, measured respectively by accelerometers and gyroscopes.
  • they can, for example, include the signal level (RSSI - Receiver Signal Strength Indicator) for the observed WiFi access points, measured by the WiFi module, three projections of the magnetic field induction vector, measured by the magnetometer, and other quantities.
  • RSSI Receiver Signal Strength Indicator
  • the measured values can be supplied with time stamps, which are stored together with the indicated output values of the sensors.
  • time stamp for example, the internal time of the processor of the mobile terminal can be used.
  • FIG. 1 depicts the process of moving a mobile terminal 191 along a continuous path 190 in a room 192.
  • a process for moving one mobile terminal is shown solely as an example, although in the general case the room may simultaneously move more than one mobile terminal. In this case, the description of the positioning process remains unchanged.
  • FIG. Figure 1 shows 5 passes along 5 paths (PO, 120, 130, 140 and 150), although the number of passes can be different. During one of these passes, the mobile terminal was moved along trajectory 110 through position 101 in the direction
  • the mobile terminal moved along trajectory 120, first through position 103 in direction 122, then through position 101 in direction 121. During several more passes, the mobile terminal was moved through position 101 along path 130 in direction 131 and along path 140 in direction 141. These fragments of the trajectory do not contain a passage through position 103. During another passage, the mobile terminal was moved through position 103 along trajectory 150 in direction 151. Directions 111, 121, 131, 141 along which the mobile was moved The terminal through position 101, as well as the motion paths of the mobile terminal 130, 140, are described in the local coordinate system 102 associated with position 101.
  • the directions 112, 122, 152 along which the mobile terminal was moved through position 103, as well as the motion path of the mobile terminal 150 are described in the local coordinate system 104, associated with the position 103.
  • the trajectories of the software and 120 are described both in the coordinate system 102, and in the coordinate system 104.
  • the signs of Ck are detected by the output signals of the non-inertial sensors of the mobile terminal, where k varies in the range from 1 to N, which makes it possible to identify the location of the mobile terminal at a certain position P, the coordinates of which in general can be unknown.
  • the following expression is used: "finding a mobile terminal in the position of Rk.” Since the position Pk can be identified with a certain accuracy, the above expression, as well as similar expressions, means that the mobile terminal is actually located in some neighborhood of the position Pk, and the radius R of the neighborhood depends on the accuracy of determining a well identifiable position. The specific value of R may vary for different applications.
  • the value of R may be one meter or units of meters.
  • the value of R can be units of decimeters or even centimeters. A further description of the proposed method is applicable for any positioning accuracy.
  • Signs that make it possible to determine with high reliability the location of the mobile terminal in a certain place of the premises can be of natural origin, but can also be formed artificially.
  • the signs can be scalar, for example, the pressure measured by the barometer, vector, for example, a three-dimensional vector of the magnetic field strength from the output of the magnetometer, or matrix and even sequences of matrices, for example, an image or video from the output of the camera.
  • a feature may be a sequence of scalar, vector, or matrix measurements over a specific time interval. For example, in a number of places in room 192, a significant change in the magnetic induction vector can be observed.
  • the magnetic induction vector when the mobile terminal 191 moves along a path 190 passing through certain positions will write out a strictly defined curve that differs from similar curves obtained when the mobile terminal moves in other places of the room or in the same place, but along a different path.
  • the unique sequence of values of the magnetic induction vector observed in this place can be considered a signature that unambiguously indicates the sequential passage of certain positions by the mobile terminal.
  • a signature that unambiguously indicates the passage by a user or other moving object of a certain part of the room can be a unique sequence of data from a short-range beacon, for example, an NFC tag.
  • a beacon signal based on BLE technology for example, iBeacon. Identification of the location of the mobile terminal in a certain position can also be provided using other positioning radio beacons, if they are located in the building or outside it.
  • Fixing a specific location of a mobile terminal can also be achieved by decoding a QR code placed as a tag in the room and containing location information, or by determining the image belonging to a characteristic part of the room. In both cases, images are obtained using the camera of the mobile terminal.
  • Another example of position fixation may be entering a position by a user via the touch screen of a mobile terminal.
  • the signs used to identify different well-identifiable indoor positions can have a different physical nature. For example, one is good an identifiable position in the room can be determined by a unique magnetic field strength vector, and another position can be determined by an NFC signal or by a QR code.
  • the position of Pk in the general case, may be unknown.
  • the sign C (ti) is received from the sensors of the mobile terminal, designated 201.
  • the sign C (t 2 ), designated as 203. for example, assume that the measured feature C (ti) at time t coincides with the previously selected feature Cb and the measured feature C (t 2) at time t 2 coincided with the previously selected feature C 2. Then we can conclude that the position of the mobile terminal 207 at the time coincides with previously identified by the position Pj (202), and the position of the mobile terminal 208 at time t 2 coincides with the previously identified position P 2 (204).
  • a fragment of the trajectory of the mobile terminal 213 and 214 is calculated in the time interval including the moment of detection of the sign, respectively, t ⁇ and t 2 .
  • the direction of movement of the mobile terminal 209 and 210 at the time of detection of the sign, respectively, ti and t 2 is determined.
  • the above calculations are performed in the local coordinate system, 205 and 206, respectively, for the positions Pj and P 2 .
  • the calculated fragment of the trajectory, as well as the data collected from non-inertial sensors collected at that time, are stored in the memory device.
  • a local coordinate system we will further consider the Cartesian coordinate system on the plane, although consideration can be carried out both for three-dimensional space and for another coordinate system, for example, polar or spherical.
  • the center of the local coordinate system associated with a well-identified position can be located near the specified position, and in the particular case, it can coincide with the specified position.
  • the axes of the local coordinate system are directed in a known manner. For example, the x-axis direction of the local coordinate system may coincide with the direction of the magnetic induction vector in the center of the local coordinate system.
  • the memory device can be located both on the mobile terminal itself, and on a remote server or cloud resource. The latter is advisable if the room simultaneously moves and participates in the described process of positioning more than one mobile terminal. In this case, communication between the mobile terminal and the remote memory is implemented using a wireless communication line.
  • the shift parameters of the local coordinate systems of the mobile terminal at the positions Pj and Pj corresponding to the identified signs Ci and Q are determined.
  • the possibility of calculating the motion path is checked a mobile terminal between the times at which the first, then the second, sign was subsequently detected. Then, if the opportunity is confirmed, the trajectory of the mobile terminal at a given time interval relative to a certain starting point is calculated and the transformation parameters of the second local coordinate system relative to the first local coordinate system are determined from the received positions.
  • Vt Vt-i + f t sin (0 t ), (2)
  • t is the time, which, without loss of generality, can be put integer
  • xt and Yg are the coordinates of the mobile terminal, calculated in the first local coordinate system (102)
  • Q t is the course (direction of movement) in the local coordinate system 102.
  • step length l t can be implemented based on data from accelerometers, and the direction of motion 9 t can be determined based on data from magnetic compass and gyroscope, as described, for example, in section 10 of the book “Principles of GNSS, Inertial, and Multisensor Integrated Navigation Systems", by PD Groves, Artech House, 2008.
  • the transformation of local coordinate systems is illustrated in FIG. 3.
  • the transformation of local coordinate systems is determined by the parameters of the displacement of the origin of the second coordinate system relative to the first, respectively, a (320) and b (321), and the angle of rotation of the second local system relative to the first system ⁇ (322).
  • the displacement parameters can be expressed from the well-known relations given, for example, in section 1.4 of Vaisman I., “Analytical Geometry”, “World Scientific Publishing”, 1997:
  • x 2 and y 2 are the coordinates of the point P 2 in the second coordinate system 311,
  • ⁇ is the angle of rotation of the second local coordinate system relative to the first.
  • the rotation angle ⁇ of the second local coordinate system relative to the first can be determined, for example, as the difference in the measurements of the magnetic compass of the mobile terminal taken at time t 2 and ti.
  • the transformation parameters (a, b, ⁇ ) of the local coordinate systems of the mobile terminal are averaged over the set of trajectories.
  • the specified averaging can be implemented as follows.
  • the calculated shift parameters of the second system the coordinates relative to the first are saved, the previous stored values of the offset parameters for these coordinate systems are searched in the memory device, the found and new offset parameters are averaged.
  • the data collected by different users using mobile terminals with different sensors is subjected to averaging. Due to this, the error in estimating the coordinate transformation parameters is reduced.
  • the spread of the parameters of the sensors of the mobile terminal is detected and, taking into account the revealed statistics, average the data collected from the same sensors. These operations are performed for each pair of detected features from the set Cb ..C. As a result, a set of N points is determined, characterized by unique features, the coordinates of which relative to each other are known with sufficient accuracy.
  • Further coordinates of the positions PI ,. .., PN, estimated in local coordinate systems, are converted to the global coordinate system.
  • the geodetic coordinate system WGS 84 can act as a global coordinate system.
  • the building coordinate system can act as a global coordinate system.
  • at least one of these points can be located outdoors, so that its global coordinates can be determined using the GPS / GNSS receiver, which is part of the mobile terminal.
  • the global coordinates of one of these points can be determined by identifying a signal transmitted from a short-range beacon, for example, an NFC tag, or a beacon operating on the basis of BLE technology, for example, iBeacon, provided that such beacons are installed in the building.
  • the beacon signal is received by the appropriate module (NFC or BLE) of the mobile terminal.
  • Another example is the determination of the global coordinates of one of these points by decoding a QR code located in the room and containing location information.
  • the QR code is read through the camera of the mobile terminal.
  • the global coordinates of at least one of the points from the set of P 1 become known P 2 , PN
  • the calculation of the global coordinates of the remaining points through known relative coordinates is not difficult. Thanks to the operations described above, the stored data from non-inertial sensors along with the calculated fragments of the trajectories of the mobile terminal are in the memory device.
  • the points P P 2 , ..., P N acquire global coordinates.
  • the local coordinates of fragments of trajectories passing through these points are converted into global coordinates.
  • data from non-inertial sensors obtained at different points of the motion paths turn out to be tied to the global coordinates of the room.
  • An example of data from non-inertial sensors can be the induction of a magnetic field, as measured by a magnetometer of a mobile terminal.
  • the set of measurements of the magnetic field at different points in the room is called a magnetic card.
  • Another example of data from non-inertial sensors is the signal strength (RSSI) from various WiFi access points, as measured by the WiFi module of the mobile terminal.
  • the set of measurements of the radio signal level for different WiFi access points at different points in the room is called WiFi radio card.
  • maps and other physical quantities measured by the sensors of the mobile terminal can be compiled. Cards collected in this way are used at the next stage of the described method for positioning a mobile terminal.
  • the position of the mobile terminal is evaluated.
  • PF Particle Filter
  • the essence of the PF algorithm is as follows. Randomly generated M objects called particles (there is no established Russian term yet, you can use the word "particles" or "samples”). Each particle can be considered as the coordinate of the object, i.e. in this example as a pair of Cartesian coordinates (x t> yi.) - D For each particle is assigned weight and / £ depending on the value of the probability density for a given coordinate. Knowing the motion model, on the basis of inertial sensors they generate a new set of particles by moving them to new positions. Thus, the forecast stage in PF is realized. Then a measurement is made (e.g. Wi-Fi radio field induction, magnetic field strength, map) and based on it, correction (refinement) of particles weights is performed.
  • a measurement e.g. Wi-Fi radio field induction, magnetic field strength, map
  • the forecast stage consists in applying (1) and (2) to each particle model of the object’s motion, as a result of which a new set of particles is obtained:
  • N (m, a 2 ) is the probability density function according to the Gaussian law with average m and variance ⁇ 2 .
  • l t is the stride length
  • 0 t is the course (direction of motion) determined by PDR
  • ⁇ ⁇ 2 ⁇ are the variances of the stride length and course.
  • p (z t I ⁇ 'êt,') is the likelihood function obtained on the basis of ⁇ , measurements, which may be the WiFi signal level, magnetic field strength, and other output values of non-inertial sensors.
  • the current position estimate is formed, for example, as a weighted average over all particles:
  • the position of the mobile terminal is evaluated as the mobile terminal moves further in the same room based on measurements of non-inertial sensors and previously generated maps.
  • the form of the functions f x (z t ), f y (z t ) depends on what specific measurements are used for positioning and on the evaluation method used. For example, for the case of using RSSI signal strength measurement, some methods are known from the literature, for example, A. Kushki, K. Plataniotis, A. Venetsanopoulos, "WLAN Positioning Systems", Cambridge University Press, 2012.
  • CN provide further refinement of the position estimation of the mobile terminal. For example, if the sign Ck is revealed, which makes it possible to identify the location of the mobile terminal in the Pk position, then the position refinement is performed by repeated application of the correction procedure (10).
  • the likelihood function may, for example, have the following form:
  • ⁇ is the variance of the coordinate estimate.
  • the variance estimation Oc may be small, whereby re-adjustment (10) from the likelihood function (14) will improve the positioning accuracy (reduce estimation variance).
  • a floor plan is available (previously the plan was not available).
  • Plan displays the following additional possibility of translation of local coordinate points Pi, P 2, ..., ⁇ in global coordinates, in this case, the coordinates of the building plan.
  • Plan imposes restrictions on the location of the points Pi, P2, ..., PN and the moving path of the mobile terminal between these points. Restrictions are caused by the presence of walls whose intersections are prohibited. Also some parts rooms, for example, separate rooms, may not be accessible for visiting.
  • the combination of the trajectories and the plan allows you to position the points P l5 ⁇ 2 , ..., PN and the trajectory of the mobile terminal between these points in such a way as to satisfy the restrictions imposed by the plan, Avoid crossing walls and visiting inaccessible places.
  • P After the location of points on the plane so that the coordinates of the points Pi, P 2, P are known in plan coordinates.
  • the operation of combining trajectories and a plan, taking into account restrictions can be performed in various ways. Consider, for example, a possible implementation of combining trajectories and a plan using PF.
  • Expression (15) takes into account the limitations of the plan by nullifying the weight of the particle that is trying to cross the wall.
  • paragraphs 2 and 3 If during the execution of paragraphs 2 and 3 all the weights are zeroed, then they return to paragraph 1 and set a new starting position for the point Pi in the coordinates of the plan.
  • FIG. 4 is a block diagram of a positioning system of a mobile terminal within a building that implements the positioning method described above.
  • the system operates as follows.
  • Many sensors 401 measure physical quantities during the movement of a mobile terminal inside a building.
  • the output values of the sensors enter the computer 402, which is designed to generate statistical models for measuring sensors in known positions and the current measurement in an unknown position. Examples of statistical models for measuring sensors at known positions can be the radio card described above or the magnetic card of a room. If the computer 402 has successfully generated these statistical models, then the probability calculation module 403 connected to it can estimate the probability of the mobile terminal being in one of the known positions.
  • a feature extraction module 410 a set of data stores 41 1 and a coordinate transformer 412 are added to the system.
  • the feature extraction module 410 is connected to a plurality of sensors 401.
  • the function of this module is to find in the output of the sensors such signs C ... Cm that the occurrence of the CK attribute in the sensor data will most likely identify the location of the mobile terminal at the Pk position.
  • the data from the sensors is stored in the set of data storages 41 1, and each of the storages is uniquely associated with one or more of the signs Ck and the positions of Pk.
  • FIG. 5 illustrates the use of data warehouses in the proposed positioning system of a mobile terminal. Shown are fragments of a mapped room in the form of three regions: a region 503 with a local coordinate system 502 associated with a well-identified position 501, a region 506 with a local coordinate system 505 associated with a well-identified position 504, and a region 509 with a local coordinate system 508 associated with well identified 507.
  • the orientation of the local coordinate systems 502, 505 and 508 can be uniquely determined in the global coordinate system 510. Regions 503, 506 and 509 define an approximate demarcation between the locally tografirovannymi fragments premises. While the data related to the local coordinate system 502, placed in the storage 511, the data related to the local coordinate system 505, placed in storage 512, and data related to the local coordinate system 508, in storage 513.
  • the data accumulated in the set of storages 411 are used in the coordinate transformer 412 to convert local coordinates and to calculate global coordinates, as described above.
  • the coordinates of the positions in which the output of the sensors are collected are known.
  • the specified coordinates along with the data are transmitted to a computer 402, which acquires the ability to build a map of the distribution of the output values of the sensors in the building.
  • the probability calculation module 403 calculates the probability of the mobile terminal being in one of the known positions, for example, in accordance with expressions (13) and (14).
  • a set of data warehouses 411 and a coordinate converter 412 can be located on a mobile terminal, but can also be located on a remote server or on a cloud resource. The latter is advisable if more than one mobile terminal is simultaneously moving and participating in the process of positioning in the room.
  • communication with the feature extraction module 410 and the computer 402 may be implemented via a wireless communication line.
  • Data storages can be implemented as part of random access memory (RAM - Random Access Memory) of a mobile terminal or server, depending on where the data storages are located.
  • a mobile terminal processor for example, an ARM Cortex-Ax type, can be used.
  • Other computing modules may be implemented on a processor or hardware accelerators of a mobile terminal or server.

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  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Automation & Control Theory (AREA)
  • Electromagnetism (AREA)
  • Probability & Statistics with Applications (AREA)
  • Navigation (AREA)
  • Position Fixing By Use Of Radio Waves (AREA)

Abstract

Le procédé et le système peuvent être utilisés pour le positionnement dans des bâtiments où les signaux de satellites de navigation ne sont pas accessibles. Le procédé consiste à révéler des indices identifiant l'emplacement du terminal mobile dans une position donnée à partir de données obtenue depuis au moins un capteur inertiel et non inertiel pendant le déplacement dudit au moins un terminal mobile; déterminer et sauvegarder la trajectoire de déplacement du terminal mobile dans un système de coordonnées local lié à ladite position, ainsi que des données de capteurs non inertiels; générer des paramètres moyennés statistiquement de conversion des systèmes de coordonnées locaux du terminal mobile dans les positions déterminées pendant le déplacement du terminal; générer au moins une carte de distribution des valeurs de sortie des capteurs non inertiels à partir de données obtenues lors de l'étape précédente; et déterminer la position du terminal mobile à partir des données obtenues lors de l'étape précédente. Le système comprend plusieurs capteurs de terminal mobile, un ordinateur, un module de calcul de probabilité, un module de séparation des indices, et un ensemble de stockages de données et un convertisseur de coordonnées.
PCT/RU2014/000822 2014-10-28 2014-10-28 Procédé et système de positionnement de terminal mobile dans des bâtiments Ceased WO2016068742A1 (fr)

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